PN 3

SimTech EXC 2075 Project Network 3 "Data-integrated model reduction for particles and continua"

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211 to 220 of 803 Results

PN 3A-7(Universität Stuttgart) Mar 8, 2024 Advanced Learning Strategies for Machine Learned Interatomic Potentials
Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes Feb 16, 2024 - PN3-5 Sriram, Siddharth, 2024, "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes", https://doi.org/10.18419/DARUS-3881, DaRUS, V1 The datasets and codes provided here are associated with our article entitled "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle". The main idea of the work is to develop surrogate models using the concepts of machine learning (ML) to predict the onset of wrinkling insta...
binary_classification.ipynb Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes Jupyter Notebook - 13.7 KB - MD5: dacad485cece6350acf08afa30461e19
de_instabilities.yml Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes application/x-yaml - 8.5 KB - MD5: 86f5d2848b4668165c8e936214efed7f
multiclass_classification.ipynb Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes Jupyter Notebook - 17.6 KB - MD5: 060c1d1f671f506010836b1ef8333a41
regression.ipynb Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes Jupyter Notebook - 12.2 KB - MD5: e489576c86ed8d8a49cfd1ddce73b94e
test_data.xlsx Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes MS Excel Spreadsheet - 10.8 KB - MD5: 38d6ddfd9c95816f04ff36fe609c892a
training_set.xlsx Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes MS Excel Spreadsheet - 49.1 KB - MD5: 6c91bdf877156aef53f78d71f7183601
Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement" Dec 22, 2023 - SFB 1333 C6 - Holm group, ICP Tischler, Ingo; Schlaich, Alexander; Holm, Christian, 2023, "Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement"", https://doi.org/10.18419/DARUS-3642, DaRUS, V1 The simulation scripts and the simulation data of the journal article mentioned under related publications from C6 group can be found here. The data is structured according to figures and schemes in the research article and contains the following data types: compressed (tar) text data files and python scripts. The structure within the tar file is a...
analyse.py Dec 22, 2023 - Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement" Python Source Code - 16.4 KB - MD5: 75528c32f447f4c2ee1c19e59225bd9e Calculates the selectivity from the simulation data

PN 3A-7(Universität Stuttgart)

Mar 8, 2024

Advanced Learning Strategies for Machine Learned Interatomic Potentials

Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

Feb 16, 2024 - PN3-5

Sriram, Siddharth, 2024, "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes", https://doi.org/10.18419/DARUS-3881, DaRUS, V1

The datasets and codes provided here are associated with our article entitled "Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle". The main idea of the work is to develop surrogate models using the concepts of machine learning (ML) to predict the onset of wrinkling insta...

binary_classification.ipynb

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

Jupyter Notebook - 13.7 KB -

de_instabilities.yml

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

application/x-yaml - 8.5 KB -

multiclass_classification.ipynb

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

Jupyter Notebook - 17.6 KB -

regression.ipynb

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

Jupyter Notebook - 12.2 KB -

test_data.xlsx

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

MS Excel Spreadsheet - 10.8 KB -

training_set.xlsx

Feb 16, 2024 - Data-driven analysis of structural instabilities in electroactive polymer bilayers based on a variational saddle-point principle: Datasets and ML codes

MS Excel Spreadsheet - 49.1 KB -

Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement"

Dec 22, 2023 - SFB 1333 C6 - Holm group, ICP

Tischler, Ingo; Schlaich, Alexander; Holm, Christian, 2023, "Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement"", https://doi.org/10.18419/DARUS-3642, DaRUS, V1

The simulation scripts and the simulation data of the journal article mentioned under related publications from C6 group can be found here. The data is structured according to figures and schemes in the research article and contains the following data types: compressed (tar) text data files and python scripts. The structure within the tar file is a...

analyse.py

Dec 22, 2023 - Replication data of C6 group for: "Disentanglement of surface and confinement effects for diene metathesis in mesoporous confinement"

Python Source Code - 16.4 KB -

Calculates the selectivity from the simulation data

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